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Subject Details

Dept : ECE

Sem : 5

Regul : 2019

Faculty : Arun Kumar.N

phone : 9688070556

E-mail : arunkumar.n.ece@snsct.org

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Lecture Notes

UNIT 1:

Definition of learning systems Goals and applications of machine learning

Types of Machine Learning Machine Learning Process

Terminology-Weight Space

The Curse of Dimensionality

Testing Machine

Learning Algorithms

UNIT 2:

Regression: Linear Regression

Parametric Models- Multivariate Regression Regression:

Classification: Bayesian Decision Theory parametric and non-parametric methods

K-Nearest Neighbor classifier

Decision Tree based methods for classification and Regression Ensemble methods

UNIT 3:

Clustering-K-means clustering

EM algorithm

Hierarchical Clustering

Principal Component Analysis

Probabilistic PCA

UNIT 4:

The Brain and The Neuron

Neural Networks

Perceptron-Training the perceptron

Perceptron Learning Algorithm

Multilayer Perceptron

Back Propagation Dimensionality Reduction

UNIT 5:

Convolutional Networks

Recurrent Neural Networks

Bidirectional RNNs

Deep Recurrent Networks

Recursive Neural Networks

Applications Speech Recognition

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